Gene sequence analysis of nirS and nirK, both encoding nitrite reductases, was performed on cultivated denitrifiers to assess their incidence in different bacterial taxa and their taxonomical value. Almost half of the 227 investigated denitrifying strains did not render an nir amplicon with any of five previously described primers. NirK and nirS were found to be prevalent in Alphaproteobacteria and Betaproteobacteria, respectively, nirK was detected in the Firmicutes and Bacteroidetes and nirS and nirK with equal frequency in the Gammaproteobacteria. These observations deviated from the hitherto reported incidence of nir genes in bacterial taxa. NirS gene phylogeny was congruent with the 16S rRNA gene phylogeny on family or genus level, although some strains did group within clusters of other bacterial classes. Phylogenetic nirK gene sequence analysis was incongruent with the 16S rRNA gene phylogeny. NirK sequences were also found to be significantly more similar to nirK sequences from the same habitat than to nirK sequences retrieved from highly related taxa. This study supports the hypothesis that horizontal gene transfer events of denitrification genes have occurred and underlines that denitrification genes should not be linked with organism diversity of denitrifiers in cultivation-independent studies.
In order to improve wastewater treatment processes, a need exists for tools that rapidly give detailed insight into the community structure of activated sludge, supplementary to chemical and physical data. In this study, the advantages of microarrays and quantitative polymerase chin reaction (PCR) methods were combined into a real-time PCR assay that allows the simultaneous quantification of phylogenetic and functional genes involved in nitrification and denitrification processes. Simultaneous quantification was possible along a 5-log dynamic range and with high linear correlation (R (2) > 0.98). The specificity of the assay was confirmed by cloning and sequencing analyses of PCR amplicons obtained from activated sludge. The real-time assay was validated on mixed liquid samples of different treatment plants, which varied in nitrogen removal rate. The abundance of ammonia oxidizers was in the order of magnitude of 10(6) down to 10(4) ml(-1), whereas nitrite oxidizers were less abundant (10(3)-10(1) order of magnitude). The results were in correspondence with the nitrite oxidation rate in the sludge types. As for the nirS, nirK, and nosZ gene copy numbers, their abundance was generally in the order of magnitude of 10(8)-10(5). When sludge samples were subjected to lab-scale perturbations, a decrease in nitrification rate was reflected within 18 h in the copy numbers of nitrifier genes (decrease with 1 to 5 log units), whereas denitrification genes remained rather unaffected. These results demonstrate that the method is a fast and accurate tool for the analysis of the (de)nitrifying community structure and size in both natural and engineered environmental samples.
In most natural environments as well as in engineered environments, such as wastewater treatment plants, ammonia-oxidizing bacteria (AOB) experience fluctuating substrate concentrations. Several physiological traits, such as low maintenance energy demand and decay rate, cell-to-cell communication, cell mobility, stable enzymes and RNAs, could allow AOB to maintain themselves under unfavourable circumstances. This review examines whether AOB possess such traits and how these traits might offer advantages over competing organisms such as heterotrophic bacteria during periods of starvation. In addition, within the AOB groups, differences exist in adaptation to and competitiveness under conditions of high or low ammonia or oxygen concentrations. Because these findings are of importance with regard to the ecology and activity of AOB in natural and engineered environments, concluding remarks are directed towards future research objectives that may clarify unanswered questions, thereby contributing to the general knowledge of the ecology and activity of ammonia oxidizers.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.